diff --git a/doc/modules/model_evaluation.rst b/doc/modules/model_evaluation.rst
index 2c4fcbeaf6bec..b161014f5268f 100644
--- a/doc/modules/model_evaluation.rst
+++ b/doc/modules/model_evaluation.rst
@@ -2489,11 +2489,11 @@ relative percentage error with respect to actual output.
 
 .. note::
 
-    The MAPE formula here represents a relative error and outputs a value in the
-    range [0, 1]. It is not a percentage in the range [0, 100] and a value of 100
-    does not mean 100% but 1e2. The motivation for the MAPE formula here to be in
-    the range [0, 1] is to be consistent with other error metrics in scikit-learn
-    such as `accuracy_score`.
+    The MAPE formula here does not represent the common "percentage" definition: the
+    percentage in the range [0, 100] is converted to a relative value in the range [0,
+    1] by dividing by 100. Thus, an error of 200% corresponds to a relative error of 2.
+    The motivation here is to have a range of values that is more consistent with other
+    error metrics in scikit-learn, such as `accuracy_score`.
 
     To obtain the mean absolute percentage error as per the Wikipedia formula,
     multiply the `mean_absolute_percentage_error` computed here by 100.
diff --git a/sklearn/metrics/_regression.py b/sklearn/metrics/_regression.py
index a7137bfef7db8..a0da4f9ed19cd 100644
--- a/sklearn/metrics/_regression.py
+++ b/sklearn/metrics/_regression.py
@@ -330,12 +330,11 @@ def mean_absolute_percentage_error(
 ):
     """Mean absolute percentage error (MAPE) regression loss.
 
-    Note here that the output is not a percentage in the range [0, 100]
-    and a value of 100 does not mean 100% but 1e2. Furthermore, the output
-    can be arbitrarily high when `y_true` is small (which is specific to the
-    metric) or when `abs(y_true - y_pred)` is large (which is common for most
-    regression metrics). Read more in the
-    :ref:`User Guide <mean_absolute_percentage_error>`.
+    Note that we are not using the common "percentage" definition: the percentage
+    in the range [0, 100] is converted to a relative value in the range [0, 1]
+    by dividing by 100. Thus, an error of 200% corresponds to a relative error of 2.
+
+    Read more in the :ref:`User Guide <mean_absolute_percentage_error>`.
 
     .. versionadded:: 0.24